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Quantitative Optical Microscopy: Measurement of Cellular Biophysical Features with a Standard Optical Microscope

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Published on: April 7, 2014

Towards a mobile quantitative phase imaging microscope with smartphone phase-detection sensors.

Xiangjiang Bao^1,2, Zheng-da Hu³, Lucas Kreiss¹

¹Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, USA.

Biomedical Optics Express

|May 11, 2026

Summary

Quad-Pixel Phase Gradient Imaging (QP2GI) uses smartphone camera sensors for single-shot quantitative phase imaging. This method reconstructs detailed phase maps of transparent samples from a single image, offering a cost-effective alternative to complex setups.

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Area of Science:

Optics
Biomedical Imaging
Microscopy

Background:

Quantitative phase imaging (QPI) visualizes transparent samples but often requires multi-frame acquisition or complex optical setups.
Existing QPI methods face limitations in speed and complexity, hindering widespread adoption.

Purpose of the Study:

To introduce Quad-Pixel Phase Gradient Imaging (QP2GI), a novel single-shot QPI technique.
To leverage commercial quad-pixel phase detection autofocus (PDAF) sensors for efficient phase imaging.

Main Methods:

QP2GI utilizes PDAF sensors, common in smartphones, which have microlenses covering 2x2 pixel groups.
Phase gradients in samples cause intensity imbalances across these pixel groups, enabling phase gradient derivation.
A light-propagation model was developed and validated in a customized microscopic system.

Main Results:

Quantitative phase maps were successfully reconstructed from single exposures of microbeads and biological specimens.
Low-coherence illumination was found to enhance robustness by reducing coherence-related noise.
Demonstrated the feasibility of using affordable PDAF sensors for single-frame QPI.

Conclusions:

QP2GI offers a simplified and cost-effective approach to single-shot quantitative phase imaging.
Quad-pixel PDAF sensors present a promising platform for developing accessible QPI systems.
The technique has potential applications in various fields requiring rapid, label-free imaging of transparent samples.